The O’Reilly Data Show Podcast: Rhea Liu on technology trends in China.
In this episode of the Data Show, I spoke with Rhea Liu, analyst at China Tech Insights, a new research firm that is part of Tencent’s Online Media Group. If there’s one place where AI and machine learning are discussed even more than the San Francisco Bay Area, that would be China. Each time I go to China, there are new applications that weren’t widely available just the year before. This year, it was impossible to miss bike sharing, mobile payments seemed to be accepted everywhere, and people kept pointing out nascent applications of computer vision (facial recognition) to identity management and retail (unmanned stores).
The O’Reilly Data Show Podcast: Bruno Fernandez-Ruiz on the importance of building the ground control center of the future.
In this episode of the Data Show, I spoke with Bruno Fernandez-Ruiz, co-founder and CTO of Nexar. We first met when he was leading Yahoo! technical teams charged with delivering a variety of large-scale, real-time data products. His new company is helping build out critical infrastructure for the emerging transportation sector.
While some question whether V2X communication is necessary to get to fully autonomous vehicles, Nexar is already paving the way by demonstrating how a vehicle-to-vehicle (V2V) communication network can be built efficiently. As Fernandez-Ruiz points out, there are many applications for such a V2V network (safety being the most obvious one). I’m particularly fascinated by what such a network, and the accompanying data, opens up for future, smarter cities. As I pointed out in a post on continuous learning, simulations are an important component of training AI applications. It seems reasonable to expect that the data sets collected by V2V networks will be useful for smart city planners of the future.
According to a 2014 U.N. report, 54% of the world’s population resides in urban areas, with further urbanization projected to push that share up to 66% by the year 2050. This projected surge in population has encouraged local and national leaders throughout the world to rally around “smart cities” — a collection of digital and information technology initiatives designed to make urban areas more livable, agile, and sustainable.
In smart cities, Internet of Things and industrial Internet applications, proper instrumentation, and data collection depend on sensors, mobile devices, and high-speed communication networks. Much of the private infrastructure belongs to and is operated by large telecommunication companies, and many of the interesting early applications and platforms are originating from telcos and network equipment providers.
Beyond simple counts and anomaly detection, the use of advanced techniques in machine learning and statistics opens up novel real-time applications (machine-to-machine) with no humans in the loop. Popular examples of such applications include systems that power environments like data centers, buildings and public spaces, and manufacturing (industrial Internet). Recognizing that future smart city applications will rely on disparate data — including event data (metrics from logs and time-series), unstructured data (images, audio, text), and geospatial data sources — we have planned sessions at Strata + Hadoop World Singapore that will cover advanced analytic techniques targeting these data types.
Smart city platforms represent some of the more exciting and impactful applications of real-time, intelligent big data systems. These platforms will confront many of the same challenges faced by applications in the commercial sector, including security, ethics, and governance. At Strata + Hadoop World Singapore, we’re looking forward to highlighting the intersection of communities and technologies that power our future cities.